학술논문

Demo: A Multi-Perspective Video Streaming System with Privacy Preservation in Trauma Room
Document Type
Conference
Source
2022 IEEE/ACM 7th Symposium on Edge Computing (SEC) SEC Edge Computing (SEC), 2022 IEEE/ACM 7th Symposium on. :310-312 Dec, 2022
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Head
Image recognition
Hospitals
Estimation
Streaming media
Cameras
Video surveillance
Language
Abstract
More and more hospitals are now deploying mul-tiple cameras in trauma room for a multi-perspective remote observation. but video surveillance system can cause privacy breach by showing and storing sensitive information of patients and staff. We use OpenPose which is a state-of-the-art human body skeletons estimation framework to extract 18 human key skeleton points. For privacy preservation, we can apply the image obfuscation techniques to human heads, we also can use human skeleton to replace the human body in the truth background. we proposed a head detection method based on the 5 key points of each head output from OpenPose. We applied the st-gcn algorithm to recognize human actions, we propose a interactive algorithm for multiple cameras to recognize and trace the same person in different cameras, Based on multi-view action recognition for the same person, we can take action recognition accuracy to a high level. Our experiment results prove that our proposed technique has a high performance in privacy protection applications. Now we focus on the interactive algorithm for multiple cameras.